Selected Portions of

Intelligence: Knowns and Unknowns

Report of a Task Force established by the Board of Scientific Affairs
of
the American Psychological Association
Released August 7, 1995

Ulric Neisser, PhD, Chair; Emory University

As presented by STALKING THE WILD TABOO

at http://www.lrainc.com/swtaboo/taboos/apa_01.html

[A slightly edited version was published in the American
Psychologist,
Feb 1996. Official Journal of the APA]

...

I. CONCEPTS OF INTELLIGENCE

Individuals differ from one another in their ability to understand
complex
ideas, to adapt effectively to the environment, to learn from
experience,
to engage in various forms of reasoning, to overcome obstacles by
taking
thought. Although these individual differences can be substantial, they
are never entirely consistent: a given person's intellectual
performance
will vary on different occasions, in different domains, as judged by
different
criteria. Concepts of "intelligence" are attempts to clarify and
organize
this complex set of phenomena. Although considerable clarity has been
achieved
in some areas, no such conceptualization has yet answered all the
important
questions and none commands universal assent. Indeed, when two dozen
prominent
theorists were recently asked to define intelligence, they gave two
dozen
somewhat different definitions (Sternberg & Detterman, 1986). Such
disagreements are not cause for dismay. Scientific research rarely
begins
with fully agreed definitions, though it may eventually lead to them.

This first section of our report reviews the approaches to
intelligence
that are currently influential, or that seem to be becoming so. Here
(as
in later sections) much of our discussion is devoted to the dominant psychometric
approach, which has not only inspired the most research and attracted
the
most attention (up to this time) but is by far the most widely used in
practical settings. Nevertheless, other points of view deserve serious
consideration. Several current theorists argue that there are many
different
"intelligences" (systems of abilities), only a few of which can be
captured
by standard psychometric tests. Others emphasize the role of culture,
both
in establishing different conceptions of intelligence and in
influencing
the acquisition of intellectual skills. Developmental psychologists,
taking
yet another direction, often focus more on the processes by which all
children
come to think intelligently than on measuring individual differences
among
them. There is also a new interest in the neural and biological bases
of
intelligence, a field of research that seems certain to expand in the
next
few years.

In this brief report, we cannot do full justice to even one such
approach.
Rather than trying to do so, we focus here on a limited and rather
specific
set of questions:

What are the significant conceptualizations of intelligence at this
time?
(Section I)

What do intelligence test scores mean, what do they predict, and how
well
do they predict it? (Section II)

Why do individuals differ in intelligence, and especially in their
scores
on intelligence tests? Our discussion of these questions implicates
both
genetic factors (Section III) and environmental factors (Section IV).

Do various ethnic groups display different patterns of performance on
intelligence
tests, and if so what might explain those differences? (Section V)

Public discussion of these issues has been especially vigorous since
the
1994 publication of Hermstein and Murray's The Bell Curve, a
controversial
volume which stimulated many equally controversial reviews and replies.
Nevertheless, we do not directly enter that debate. Hermstein and
Murray
(and many of their critics) have gone well beyond the scientific
findings,
making explicit recommendations on various aspects of public policy.
Our
concern here, however, is with science rather than policy. The charge
to
our Task Force was to prepare a dispassionate survey of the state of
the
art: to make clear what has been scientifically established, what is
presently
in dispute, and what is still unknown. In fulfilling that charge, the
only
recommendations we shall make are for further research and calmer
debate.

The Psychometric Approach

Ever since Alfred Binet's great success in devising tests to
distinguish
mentally retarded children from those with behavior problems,
psychometric
instruments have played an important part in European and American
life.
Tests are used for many purposes, such as selection, diagnosis, and
evaluation.
Many of the most widely used tests are not intended to measure
intelligence
itself but some closely related construct: scholastic aptitude, school
achievement, specific abilities, etc. Such tests are especially
important
for selection purposes. For preparatory school, it's the SSAT; for
college,
the SAT or ACT; for graduate school, the GRE; for medical school, the
MOAT;
for law school, the LSAT; for business school, the GMAT. Scores on
intelligence-related
tests matter, and the stakes can be high.

Intelligence tests. Tests of
intelligence
itself (in the psychometric sense) come in many forms. Some use only a
single type of item or question; examples include the Peabody Picture
Vocabulary
Test (a measure of children's verbal intelligence) and Raven's
Progressive
Matrices (a nonverbal, untimed test that requires inductive reasoning
about
perceptual patterns). Although such instruments are useful for specific
purposes, the more familiar measures of general intelligence, such as
the
Wechsler tests and the Stanford-Binet, include many different types of
items, both verbal and nonverbal. Test-takers may be asked to give the
meanings of words, to complete a series of pictures, to indicate which
of several words does not belong with the others, and the like. Their
performance
can then be scored to yield several subscores as well as an overall
score.

By convention, overall intelligence test scores are usuallv
converted
to a scale in which the mean is 100 and the standard deviation is 15.
(The
standard deviation is a measure of the variability of the distribution
of scores.) Approximately 95% of the population has scores within two
standard
deviations of the mean, i.e. between 70 and 130. For historical
reasons,
the term "IQ" is often used to describe scores on tests of
intelligence.
It originally referred to an "intelligence Quotient" that was formed by
dividing a so-called mental age by a chronological age, but this
procedure
is no longer used.

Intercorrelations among Tests.
Individuals
rarely perform equally well on all the different kinds of items
included
in a test of intelligence. One person may do relatively better on
verbal
than on spatial items, for example, while another may show the opposite
pattern. Nevertheless, subtests measuring different abilities tend to
be
positively correlated: people who score high on one such subtest are
likely
to be above average on others as well. These complex patterns of
correlation
can be clarified by factor analysis, but the results of such analyses
are
often controversial themselves. Some theorists (e.g., Spearman, 1927)
have
emphasized the importance of a general factor, g, which represents what
all the tests have in common; others (e.g., Thurstone, 1938) focus on
more
specific group factors such as memory, verbal comprehension, or number
facility. As we shall see in Section 2, one common view today envisages
something like a hierarchy of factors with g at the apex. But there is
no full agreement on what g actually means: it has been described as a
mere statistical regularity (Thompson, 1939), a kind of mental energy
(Spearman,
1927), a generalized abstract reasoning ability (Gustafsson 1984), or
an
index measure of neural processing speed (Reed & Jensen, 1992).

There have been many disputes over the utility of IQ and g. Some
theorists
are critical of the entire psychometric approach (e.g., Ceci, 1990;
Gardner,
1983; Gould, 1978), while others regard it as firmly established (e.g.,
Carroll, 1993; Eysenck, 1973; Hermstein & Murray, 1994; Jensen,
1972).
The critics do not dispute the stability of test scores, nor the fact
that
they predict certain forms of achievement-especially school
achievement--rather
effectively (see Section 2). They do argue, however, that to base a
concept
of intelligence on test scores alone is to ignore many important
aspects
of mental ability. Some of those aspects are emphasized in other
approaches
reviewed below.

Multiple Forms of Intelligence

Gardner's Theory. A relatively new
approach
is the theory of "multiple intelligences"; proposed by Howard Gardner
(1983).
On this view conceptions of intelligence should be informed not only by
work with normal children and adults but also by studies of gifted
individuals
(including so-called 'savants"), of persons who have suffered brain
damage,
of experts and virtuosos, and of individuals from diverse cultures.
These
considerations have led Gardner to include musical,
bodlily-kinesthetic,
and various forms of personal intelligence as well as more familiar
spatial,
linguistic, and logical mathematical abilities in the scope of his
theory.
He argues that psychometric tests address only linguistic and logical
plus
some aspects of spatial intelligence; other forms have been entirely
ignored.
Moreover, the paper and-pencil format of most tests rules out many
kinds
of intelligent performance that matter in everyday life, such as giving
an extemporaneous talk (linguistic) or being able to find one's way in
a new town (spatial). While Gardner's arguments have attracted
considerable
interest, the stability and validity of performance tests in these new
domains has yet to be conclusively demonstrated. It is also possible to
doubt whether some of these abilities-bodily-kinesthetic," for
example--are
appropriately described as forms of intelligence rather than as special
talents.

Sternberg's Theory. Robert Sternberg's
(1985)
triarchic theory proposes three fundamental aspects of
intelligence-analytic,
creative, and practical--of which only the first is measured to any
significant
extent by mainstream tests. His investigations suggest the need for a
balance
between analytic intelligence, on the one hand, and creative and
especially
practical intelligence on the other. The distinction between analytic
(or
"academic") and practical intelligence has also been made by others
(e.g.,
Neisser, 1976). Analytic problems, of the type suitable for test
construction,
tend to (a) have been formulated by other people, (b) be clearly
defined,
(c) come with all the information needed to solve them, (d) have only a
single right answer, which can be reached by only a single method, (e)
be disembodied from ordinary experience, and (f) have little or no
intrinsic
interest. Practical problems, in contrast, tend to (a) require problem
recognition and formulation, (b) be poorly defined, (c) require
information
seeking, (d) have various acceptable solutions, (e) be embedded in and
require prior everyday experience, and (f) require motivation and
personal
involvement.

As part of their study of practical intelligence, Sternberg and his
collaborators have developed measures of "tacit knowledge" in
various
domains, especially business management. In these measures, individuals
are given written scenarios of various work related situations and then
asked to rank a number of options for dealing with the situation
presented.
The results show that tacit knowledge predicts such criteria such as
job
performance fairly well, even though it is relatively independent of
intelligence
test scores and other common selection measures (Sternberg &
Wagner,
1993; Sternberg, Wagner, Williams & Horvath, in press). This work,
too, has its critics (Jensen, 1993; Schmidt & Hunter, 1993).

Related Findings. Other investigators
have
also demonstrated the relative independence of academic and practical
intelligence.
Brazilian street children, for example, are quite capable of doing the
math required for survival in their street business even though they
have
failed mathematics in school (Carraher, Carraher, and Schliemann,
1985).
Similarly, women shoppers in California who had no difficulty in
comparing
product values at the supermarket were unable to carry out the same
mathematical
operations in paper-and pencil tests (Lave, 1988). In a study of
expertise
in wagering on harness races, Ceci and Liker (1986) found that the
skilled
handicappers implicitly used a highly complex interactive model with as
many as seven variables; the ability to do this successfully was
unrelated
to scores on intelligence tests.

Cultural Variation.

It is very difficult to compare concepts of intelligence across
cultures.
English is not alone in having many words for different aspects of
intellectual
power and cognitive skill (wise, sensible, smart, bright, clever;
cunning,
etc.); if another language has just as many, which of them shall we
say corresponds to its speakers' "concept of intelligence"? The few
attempts
to examine this issue directly have typically found that, even within a
given society, different cognitive characteristics are emphasized from
one situation to another and from one subculture to another(Serpell,
1974;
Super, 1983; Wober, 1974). These differences extend not just to
conceptions
of intelligence but to what is considered adaptive or appropriate in a
broader sense.

These issues have occasionally been addressed across sub-cultures
and
ethnic groups in America. In a study conducted in San Jose California,
Okagaki and Sternberg (1993) asked immigrant parents from Cambodia,
Mexico,
the Philippines and Vietnam, as well as native-born Angle-Americans and
Mexican-Americans, about their conceptions of child-rearing,
appropriate
teaching, and children's intelligence. Parents from all groups except
Angle-Americans
indicated that such characteristics as motivation, social skills, and
practical
school skills were as or more important than cognitive characteristics
for
their conceptions of an intelligent first-grade child.

Heath (1983) found that different ethnic groups in North Carolina
have
different conceptions of intelligence. To be considered as intelligent
or adaptive, one must excel in the skills valued by one's own group.
One
particularly interesting contrast was in the importance ascribed to
verbal
vs. nonverbal communication skills--to saying things explicitly as
opposed
to using and understanding gestures and facial expressions. Note that
while
both these forms of communicative skill have their uses, they are not
equally
well represented in psychometric tests.

How testing is done can have different effects in different cultural
groups. This can happen for many reasons, including differential
familiarity
with the test materials themselves. Serpell (1979), for example, asked
Zambian and English children to reproduce patterns in three media: wire
models, clay models, or pencil and paper. The Zambian children excelled
in the wire medium with which they were familiar, while the English
children
were best with pencil and paper. Both groups performed equally well
with
clay.

Developmental Progressions

Piaget's Theory. The best-known
developmentally-based
conception of intelligence is certainly that of the Swiss psychologist
Jean Piaget (1972). Unlike most of the theorists considered here,
Piaget
had relatively little interest in individual differences. Intelligence
develops in all children through the continually shifting balance
between
the assimilation of new information into existing cognitive structures
and the accommodation of those structures themselves to the new
information.
To index the development of intelligence in this sense, Piaget devised
methods that are rather different from conventional tests. To assess
the
understanding of "conservation." for example, (roughly, the principle
that
material quantity is not affected by mere changes of shape), children
who
have watched water being poured from a shallow to a tall beaker may be
asked if there is now more water than before. (A positive answer would
suggest that the child has not yet mastered the principle of
conservation.)
Piaget's tasks can be modified to serve as measures of individual
differences;
when this is done, they correlate fairly well with standard
psychometric
tests (for a review see Jensen, 1980).

Vygotsky's Theory. The Russian
psychologist
Lev Vygotsky (1978) argued that all intellectual abilities are social
in
origin. Language and thought first appear in early interactions with
parents,
and continue to develop through contact with teachers and others.
Traditional
intelligence tests ignore what Vygotsky called the "zone of proximal
development."
i.e., the level of performance that a child might reach with
appropriate
help from a supportive adult. Such tests are "static." measuring only
the
intelligence that is already fully developed. "Dynamic" testing, in
which
the examiner provides guided and graded feedback, can go further to
give
some indication of the child's latent potential. These ideas are being
developed and extended by a number of contemporary psychologists (Brown
& French, 1979; Feuerstein, 1980; Pascual-Leone & Ijaz, 1989).

Biological Approaches

Some investigators have recently turned to the study of the brain as a
basis for new ideas about what intelligence is and how to measure it.
Many
aspects of brain anatomy and physiology have been suggested as
potentially
relevant to intelligence: the arborization of cortical neurons (Ceci,
1990),
cerebral glucose metabolism (Haier 1993), evoked potentials (Caryl,
1994),
nerve conduction velocity (Reed & Jensen, 1992), sex hormones (see
Section 4), and still others (cf. Vernon, 1993). Advances in research
methods,
including new forms of brain imaging such as PET and MRI scans, will
surely
add to this list. In the not-too-distant future it may be possible to
relate
some aspects of test performance to specific characteristics of brain
function.

This brief survey has revealed a wide range of contemporary
conceptions
of intelligence and of how it should be measured. The psychometric
approach
is the oldest and best established, but others also have much to
contribute.
We should be open to the possibility that our understanding of
intelligence
in the future will be rather different from what it is today.

II INTELLIGENCE TESTS AND THEIR CORRELATES

...

Tests as Predictors

School Performance. Intelligence tests
were
originally devised by Alfred Binet to measure children's ability to
succeed
in school. They do in fact predict school performance fairly well: the
correlation between IS scores and grades is about .50. They also
predict
scores on school achievement tests, designed to measure knowledge of
the
curriculum. Note, however, that correlations of this magnitude account
for only about 25% of the overall variance. Successful school learning
depends on many personal characteristics other than intelligence, such
as persistence, interest in school, and willingness to study. The
encouragement
for academic achievement that is received from peers, family and
teachers
may also be important, together with more general cultural factors (see
Section 5).

The relationship between test scores and school performance seems to
be ubiquitous. Wherever it has been studied, children with high scores
on tests of intelligence tend to learn more of what is taught in school
than their lower-scoring peers. There may be styles of teaching and
methods
of instruction that will decrease or increase this correlation, but
none
that consistently eliminates it has yet been found (Cronbach and Snow,
1977).

What children learn in school depends not only on their individual
abilities
but also on teaching practices and on what is actually taught. Recent
comparisons
among pupils attending school in different countries have made this
especially
obvious. Children in Japan and China, for example, know a great deal
more
math than American children even though their intelligence test scores
are quite similar (see Section 5). This difference may result from many
factors, including cultural attitudes toward schooling as well as the
sheer
amount of time devoted to the study of mathematics and how that study
is
organized (Stevenson & Stigler, 1992). In principle it is quite
possible
to improve the school learning of American children--even very
substantially-without
changing their intelligence test scores at all.

Years of Education. Some children stay
in
school longer than others; many go on to college and perhaps beyond.
Two
variables that can be measured as early as elementary school correlate
with the total amount of education individuals will obtain: test scores
and social class background. Correlations between IQ scores and total
years
of education are about .55, implying that differences in psychometric
intelligence
account for about 30% of the outcome variance. The correlations of
years
of education with social class background (as indexed by the
occupation/
education of a child's parents) are also positive, but somewhat lower.

There are a number of reasons why children with higher test scores
tend
to get more education. They are likely to get good grades, and to be
encouraged
by teachers and counselors; often they are placed in "college
preparatory"
classes, where they make friends who may also encourage them. In
general,
they are likely to find the process of education rewarding in a way
that
many low-scoring children do not (Rehberg and Rosenthal, 1978). These
influences
are not omnipotent: some high scoring children do drop out of school.
Many
personal and social characteristics other than psychometric
intelligence
determine academic success and interest, and social privilege may also
play a role. Nevertheless, test scores are the best single predictor of
an individual's years of education.

In contemporary American society, the amount of schooling that
adults
complete is also somewhat predictive of their social status.
Occupations
considered high in prestige (e.g., law, medicine, even corporate
business)
usually require at least a college degree-16 or more years of
education-as
a condition of entry. It is partly because intelligence test scores
predict
years of education so well that they also predict occupational status,
and even income to a smaller extent, (Jencks, 1979). Moreover, many
occupations
can only be entered through professional schools which base their
admissions
at least partly on test scores: the MCAT, the GMAT, the LSAT, etc.
Individual
scores on admission-related tests such as these are certainly
correlated
with scores on tests of intelligence.

Social Status and Income. How well do
IQ
scores (which can be obtained before individuals enter the labor force)
predict such outcome measures as the social status or income of adults?
This question is complex, in part because another variable also
predicts
such outcomes: namely, the socioeconomic status (SES) of one's parents.
Unsurprisingly, children of privileged families are more likely to
attain
high social status than those whose parents are poor and less educated.
These two predictors (IQ and parental SES) are by no means independent
of one another; the correlation between them is around .33 (White,
1982).

One way to look at these relationships is to begin with SES.
According
to Jencks (1979), measures of parental SES predict about one-third of
the
variance in young adults' social status and about one-fifth of the
variance
in their income. About half of this predictive effectiveness depends on
the fact that the SES of parents also predicts children's intelligence
test scores, which have their own predictive value for social outcomes;
the other half comes about in other ways.

We can also begin with IQ scores, which by themselves account for
about
one-fourth of the social status variance and one-sixth of the income
variance.
Statistical controls for parental SES eliminate only about a quarter of
this predictive power. One way to conceptualize this effect is by
comparing
the occupational status (or income) of adult brothers who grew up in
the
same family and hence have the same parental SES. In such cases, the
brother
with the higher adolescent IQ score is likely to have the higher adult
social status and income (Jencks, 1979). This effect, in turn, is
substantially
mediated by education: the brother with the higher test scores is
likely
to get more schooling, and hence to be better credentialled as he
enters
the workplace.

Do these data imply that psychometric intelligence is a major
determinant
of social status or income? That depends on what one means by major. In
fact, individuals who have the same test scores may differ widely in
occupational
status and even more widely in income. Consider for a moment the
distribution
of occupational status scores for all individuals in a population, and
then consider the conditional distribution of such scores for just
those
individuals who test at some given I8. Jencks (1979) notes that the
standard
deviation of the latter distribution may still be quite large; in some
cases it amounts to about 88% of the standard deviation for the entire
population. Viewed from this perspective, psychometric intelligence
appears
as only one of a great many factors that influence social outcomes.

Job Performance. Scores on
intelligence
tests predict various measures of job performance: supervisor ratings,
work samples, etc. Such correlations, which typically lie between r=.30
and r=.50, are partly restricted by the limited reliability of those
measures
themselves. They become higher when ris statistically corrected for
this
unreliability: in one survey of relevant studies (Hunter, 1983), the
mean
of the corrected correlations was .54. This implies that, across a wide
range of occupations, intelligence test performance accounts for some
29%
of the variance in job performance.

Although these correlations can sometimes be modified by changing
methods
of training or aspects of the job itself, intelligence test scores are
at least weakly related to job performance in most settings. Sometimes
19 scores are described as the 'best available predictor" of that
performance.
It is worth noting, however, that such tests predict considerably less
than half the variance of job-related measures. Other individual
characteristics
such as interpersonal skills, aspects of personality, etc., are
probably
of equal or greater importance, but at this point we do not have
equally
reliable instruments to measure them.

Social Outcomes. Psychometric
intelligence
is negatively correlated with certain socially undesirable outcomes.
For
example, children with high test scores are less likely than
lower-scoring
children to engage in juvenile crime. in one study, Moffitt, Gabrielli,
Mednick & Schulsinger (1981) found a correlation of -.19 between IQ
scores and number of juvenile offenses in a large Danish sample; with
social
class controlled, the correlation dropped to -. 17. The correlations
for
most "negative outcome" variables are typically smaller than .20, which
means that test scores are associated with less than 4% of their total
variance. It is important to realize that the causal links between
psychemetric
ability and social outcomes may be indirect. Children who are
unsuccessful
in-and hence alienated from-school may be more likely to engage in
delinquent
behaviors for that very reason, compared to other children who enjoy
school
and are doing well.

In summary, intelligence test scores predict a wide range of social
outcomes with varying degrees of success. Correlations are highest for
school achievement, where they account for about a quarter of the
variance.
They are somewhat lower for job performance, and very low for
negatively
valued outcomes such as criminality. In general, intelligence tests
measure
only some of the many personal characteristics that are relevant to
life
in contemporary America. Those characteristics are never the only
influence
on outcomes, though in the case of school performance they may well be
the strongest.

...

III. THE GENES AND INTELLIGENCE

In this section of the report we first discuss individual differences
generally,
without reference to any particular trait. We then focus on
intelligence,
as measured by conventional IQ tests or other tests intended to measure
general cognitive ability. The different and more controversial topic
of
group differences will be considered in Section V.

We focus here on the relative contributions of genes and
environments
to individual differences in particular traits. To avoid
misunderstanding,
it must be emphasized from the outset that gene action always involves
an environment--at least a biochemical environment, and often an
ecological
one. (For humans, that ecology is usually interpersonal or cultural.)
Thus
all genetic effects on the development of observable traits are
potentially
modifiable by environmental input, though the practicability of making
such modifications may be another matter. Conversely, all environmental
effects on trait development involve the genes or structures to which
the
genes have contributed. Thus there is always a genetic aspect to the
effects
of the environment (cf. Plomin & Bergeman, 1991).

Sources of Individual Differences

Partitioning the Variation. Individuals
differ
from one another on a wide variety of traits: familiar examples include
height. intelligence, and aspects of personality. Those differences are
often of considerable social importance. Many interesting questions can
be asked about their nature and origins. One such question is the
extent
to which they reflect differences among the genes of the individuals
involved,
as distinguished from differences among the environments to which those
individuals have been exposed. The issue here is not whether genes and
environments are both essential for the development of a given trait
(this
is always the case), and it is not about the genes or environment of
any
particular person. We are concerned only with the observed variation of
the trait across individuals in a given population. A figure called the
"heritability" (h2) of the trait represents the proportion
of
that variation that is associated with genetic differences among the
individuals.
The remaining variation (1 - h2] is associated with
environmental
differences and with errors of measurement. These proportions can be
estimated
by various methods described below.

Sometimes special interest attaches to those aspects of environments
that family members have in common (for example, characteristics of the
home). The part of the variation that derives from this source, called
"shared" variation or c2, can also be estimated....

A high heritability does not mean that the environment has no impact
on the development of a trait, or that learning is not involved.
Vocabulary
size, for example, is very substantially heritable (and highly
correlated
with general intelligence) although every word in an individual's
vocabulary
is learned. In a society in which plenty of words are available in
everyone's
environment, especially for individuals who are motivated to seek them
out, the number of words that individuals actually learn depends to a
considerable
extent on their genetic predispositions.

...

How Genetic Estimates are Made.
Estimates
of the magnitudes of these sources of individual differences are made
by
exploiting natural and social 'experiments" that combine genotypes and
environments in informative ways. Monozygotic (MZ) and dyzygotic (DZ)
twins,
for example, can be regarded as experiments of nature. MZ twins are
paired
individuals of the same age growing up in the same family who have all
their genes in common; DZ twins are otherwise similar pairs who have
only
half their genes in common. Adoptions, in contrast, are experiments of
society. They allow one to compare genetically unrelated persons who
are
growing up in the same family as well as genetically related persons
who
are growing up in different families. They can also provide information
about genotype-environment correlations: in ordinary families genes and
environments are correlated because the same parents provide both,
whereas
in adoptive families one set of parents provides the genes and another
the environment. An experiment involving both nature and society is the
study of monozygotic twins who have been reared apart (Bouchard,
Lykken,
McGue, Segal & Tellegen, 1990; Pedersen, Plomin, Nesselroade &
McClearn, 1992). Relationships in the families of monozygotic twins
also
offer unique possibilities for analysis (e.g., Rose, Harris, Christian,
& Nance, 1979). Because these comparisons are subject to different
sources of potential error, the results of studies involving several
kinds
of kinship are often analyzed together to arrive at robust overall
conclusions.
(For general discussions of behavior genetic methods, see Plomin,
DeFries,
& McClearn, 1990, or Hay, 1985.)

Results for IQ scores

Parameter Estimates. Across the ordinary
range
of environments in modern Western societies, a sizable part of the
variation
in intelligence test scores is associated with genetic differences
among
individuals. Quantitative estimates vary from one study to another,
because
many are based on small or selective samples. If one simply combines
all
available correlations in a single analysis, the heritability (h2)
works out to about .50 and the between-family variance (c2)
to about .25 (e.g., Chipuer, Rovine, & Plomin, 1990; Loehlin,
1989).
These overall figures are misleading, however, because most of the
relevant
studies have been done with children. We now know that the heritability
of IQ changes with age: h2 goes up and c2 goes
down
from infancy to adulthood (McCartney, Harris, & Bernieri, 1990;
McGue,
Bouchard, Iacono, & Lykken, 1993). In childhood h2 and C2
for IQ are of the order of .45 and .35; by late adolescence h2
is around .75 and c2 is quite low (zero in some studies).
Substantial
environmental variance remains, but it primarily reflects within-family
rather than between-family differences.

...

Implications. Estimates of h2
and c2 for IQ (or any other trait) are descriptive
statistics
for the populations studied. (In this respect they are like means and
standard
deviations.) They are outcome measures, summarizing the results of a
great
many diverse, intricate, individually variable events and processes,
but
they can nevertheless be quite useful. They can tell us how much of the
variation in a given trait the genes and family environments explain,
and
changes in them place some constraints on theories of how this occurs.
On the other hand they have little to say about specific mechanisms,
i.e.
about how genetic and environmental differences get translated into
individual
physiological and psychological differences. Many psychologists and
neuroscientists
are actively studying such processes; data on heritabilities may give
them
ideas about what to look for and where or when to look for it.

A common error is to assume that because something is heritable it
is
necessarily unchangeable This is wrong. Heritability does not imply
immutability.
As previously noted, heritable traits can depend on learning, and they
may be subject to other environmental effects as well.

...

IV. ENVIRONMENTAL EFFECTS ON INTELLIGENCE

The 'environment" includes a wide range of influences on intelligence.
Some of those variables affect whole populations, while others
contribute
to individual differences within a given group. Some of them are
social,
some are biological; at this point some are still mysterious. It may
also
happen that the proper interpretation of an environmental variable
requires
the simultaneous consideration of genetic effects. Nevertheless, a good
deal of solid information is available.

Social Variables

It is obvious that the cultural environment - how people live, what
they
value, what they do - has a significant effect on the intellectual
skills
developed by individuals. Rice farmers in Liberia are good at
estimating
quantities of rice (Gay & Cole, 1967); children in Botswana,
accustomed
to storytelling, have excellent memories for stories (Dube, 1982). Both
these groups were far ahead of American controls on the tasks in
question.
On the other hand Americans and other Westernized groups typically
outperform
members of traditional societies on psychometric tests, even those
designed
to be "culture-fair."

Cultures typically differ from one another in so many ways that
particular
differences can rarely be ascribed to single causes. Even comparisons
between
subpopulations are often difficult to interpret. If we find that groups
living in different environments (e.g., middle-class and poor
Americans)
differ in their test scores, it is easy to suppose that the
environmental
difference causes the IQ difference. But there is also an opposite
direction
of causation: individuals may come to be in one environment or another
because of differences in their own abilities, including the abilities
measured by intelligence tests. Waller (1971) has shown, for example,
that
sons whose IQ scores are above those of their fathers also tend to
achieve
a higher social class status; conversely, those with scores below their
fathers' tend to achieve lower status. Such an effect is not
surprising,
given the relation between IQ scores and years of education reviewed in
Section II.

Occupation. In section II we noted
that
intelligence test scores predict occupational level, not only because
some
occupations require more intelligence than others but also because
admission
to many professions depends on test scores in the first place. There
can
also be an effect in the opposite direction, i.e. workplaces may affect
the intelligence of those who work in them. Kohn and Schooler (1973),
who
interviewed some 3000 men in various occupations (farmers, managers,
machinists,
porters...), argued that more "complex" jobs produce more "intellectual
flexibility" in the individuals who hold them. Although the issue of
direction
of effects complicates the interpretation of their study, this remains
a plausible suggestion.

Among other things, Kohn & Schooler's hypothesis may help us
understand
urban/rural differences. A generation ago these were substantial in the
United States, averaging about six IQ points or 0.4 standard deviations
(Terman & Merrill, 1937; Seashore, Wesman & Doppelt, 1950). In
recent years the difference has declined to about two points (Kaufman
&
Doppelt, 1976; Reynolds, Chastain, Kaufman & McLean, 1987). In all
likelihood this urban/ rural convergence primarily reflects
environmental
changes: a decrease in rural isolation (due to increased travel and
mass
communications), an improvement in rural schools, the greater use of
technology
on farms. All these changes can be regarded as increasing the
"complexity"
of the rural environment in general or of farm work in particular.
(However,
processes with a genetic component, e.g., changes in the selectivity of
migration from farm to city, cannot be completely excluded as
contributing
factors.)

Schooling. Attendance at school is
both
a dependent and an independent variable in relation to intelligence. On
the one hand, children with higher test scores are less likely to drop
out, more likely to be promoted from grade to grade and then to attend
college. Thus the number of years of education that adults complete is
roughly predictable from their childhood scores on intelligence tests.
On the other hand schooling itself changes mental abilities, including
those abilities measured on psychometric tests. This is obvious for
tests
like the SAT that are explicitly designed to assess school learning,
but
it is almost equally true of intelligence tests themselves.

The evidence for the effect of schooling on intelligence test scores
takes many forms (Ceci, 1991). When children of nearly the same age go
through school a year apart (because of birthday-related admission
criteria),
those who have been in school longer have higher mean scores. Children
who attend school intermittently score below those who go regularly,
and
test performance tends to drop over the summer vacation. A striking
demonstration
of this effect appeared when the schools in one Virginia county closed
for several years in the 1960s to avoid integration, leaving most Black
children with no formal education at all. Compared to controls, the
intelligence-test
scores of these children dropped by about 0.4 standard deviations (6
points)
per missed year of school (Green et al, 1964).

Schools affect intelligence in several ways, most obviously by
transmitting
information. The answers to questions like "Who wrote Hamlet?" and
"What
is the boiling point of water?" are typically learned in school, where
some pupils learn them more easily and thoroughly than others. Perhaps
at least as important are certain general skills and attitudes:
systematic
problem-solving, abstract thinking, categorization, sustained attention
to material of little intrinsic interest, repeated manipulation of
basic
symbols and operations. There is no doubt that schools promote and
permit
the development of significant intellectual skills, which develop to
different
extents in different children. It is because tests of intelligence draw
on many of those same skills that they predict school achievement as
well
as they do.

To achieve these results, the school experience must meet at least
some
minimum standard of quality. In very poor schools, children may learn
so
little that they fall farther behind the national IQ norms for every
year
of attendance. When this happens, older siblings have systematically
lower
scores than their younger counterparts. This pattern of scores appeared
in at least one rural Georgia school system in the 1970s (Jensen,
1977).
Before desegregation, it must have been characteristic of many of the
schools
attended by Black pupils in the South. In a study based on Black
children
who had moved to Philadelphia at various ages during this period, Lee
(1951)
found that their IQ scores went up more than half a point for each year
that they were enrolled in the Philadelphia system.

Interventions. Intelligence test
scores
reflect a child's standing relative to others in his or her age cohort.
Very poor or interrupted schooling can lower that standing
substantially;
are there also ways to raise it? In fact many interventions have been
shown
to raise test scores and mental ability 'in the short run" (i.e. while
the program itself was in progress), but long-run gains have proved
more
elusive. One noteworthy example of (at least short-run) success was the
Venezuelan Intelligence Project (Hermstein et al, 1986), in which
hundreds
of seventh-grade children from underprivileged backgrounds in that
country
were exposed to an extensive, theoretically based curriculum focused on
thinking skills. The intervention produced substantial gains on a wide
range of tests, but there has been no follow-up.

Children who participate in "Head Start" and similar programs are
exposed
to various school-related materials and experiences for one or two
years.
Their test scores often go up during the course of the program, but
these
gains fade with time. By the end of elementary school, there are
usually
no significant I9 or achievement-test differences between children who
have been in such programs and controls who have not. There may,
however,
be other differences. Follow-up studies suggest that children who
participated
in such programs as preschoolers are less likely to be assigned to
special
education, less likely to be held back in grade, and more likely to
finish
high school than matched controls (Consortium for Longitudinal Studies,
1983; Darlington, 1986; but see Locurto, 1991).

More extensive interventions might be expected to produce larger and
more lasting effects, but few such programs have been evaluated
systematically.
One of the more successful is the Carolina Abecedarian Project
(Campbell
& Ramey, 1994), which provided a group of children with enriched
environments
from early infancy through preschool and also maintained appropriate
controls.
The test scores of the enrichment-group children were already higher
than
those of controls at age two; they were still some five points higher
at
age twelve, seven years after the end of the intervention. Importantly,
the enrichment group also outperformed the controls in academic
achievement.

Family environment. No one doubts that
normal
child development requires a certain minimum level of responsible care.
Severely deprived, neglectful, or abusive environments must have
negative
effects on a great many aspects of development, including intellectual
aspects. Beyond that minimum, however, the role of family experience is
now in serious dispute (Baumrind, 1993; Jackson, 1993; Scarr, 1992,
1993).
Psychometric intelligence is a case in point. Do differences between
children's
family environments (within the normal range) produce differences in
their
intelligence test performance? The problem here is to disentangle
causation
from correlation. There is no doubt that such variables as resources of
the home (Gottfried, 1984) and parents' use of language (Hart &
Risley,
1992, in press) are correlated with children's IQ scores, but such
correlations
may be mediated by genetic as well as (or instead of) environmental
factors.

...

These findings suggest that differences in the life styles of
families
whatever their importance may be for many aspects of children's lives
make
little long-term difference for the skills measured by intelligence
tests.
We should note, however, that low-income and non-white families are
poorly
represented in existing adoption studies as well as in most twin
samples.
Thus it is not yet clear whether these surprisingly small values of
(adolescent)
c2 apply to the population as a whole. It re-mains possible
that, across the full range of income and ethnicity, between-family
differences
have more lasting consequences for psychometric intelligence.

Biological Variables

Every individual has a biological as well as a social environment, one
that begins in the womb and extends throughout life. Many aspects of
that
environment can affect intellectual development. We now know that a
number
of biological factors, including malnutrition, exposure to toxic
substances,
and various prenatal and perinatal stressors, result in lowered
psychometric
intelligence under at least some conditions.

Nutrition. There has been only one
major
study of the effects of prenatal malnutrition (i.e. malnutrition of the
mother during pregnancy) on long-term intellectual development. Stein
et
al (1975) analyzed the test scores of Dutch 19-year-old males in
relation
to a wartime famine that had occurred in the winter of 1944-45, just
before
their birth. In this very large sample (made possible by a universal
military
induction requirement), exposure to the famine had no effect on adult
intelligence.
Note, however, that the famine itself lasted only a few months; the
subjects
were exposed to it prenatally but not after birth.

In contrast, prolonged malnutrition during childhood does have
long-term
intellectual effects. These have not been easy to establish, in part
because
many other unfavorable socioeconomic conditions are often associated
with
chronic malnutrition (Ricciuti, 1993; but cf. Sigman, 1995). In one
intervention
study, however, pre-schoolers in two Guatemalan villages (where
undernourishment
is common) were given ad lib access to a protein dietary supplement for
several years. A decade later, many of these children (namely, those
from
the poorest socio-economic levels) scored significantly higher on
school
related achievement tests than comparable controls (Pollitt et al,
1993).
It is worth noting that the effects of poor nutrition on intelligence
may
well be indirect. Malnourished children are typically less responsive
to
adults, less motivated to learn, and less active in exploration than
their
more adequately nourished counterparts.

...

Lead. Certain toxins have well
established
negative effects on intelligence. Exposure to lead is one such factor.
In one long-term study (McMichael et al, 1988; Baghurst et al, 1992),
the
blood lead levels of children growing up near a lead smelting plant
were
substantially and negatively correlated with intelligence test scores
throughout
childhood. No "threshold dose" for the effect of lead appears in such
studies.
Although ambient lead levels in the United States have been reduced in
recent years, there is reason to believe that some American children -
especially those in inner cities - may still be at risk from this
source
(cf. Needleman, Geiger & Frank, 1985).

Alcohol Extensive prenatal exposure
to alcohol
(which occurs if the mother drinks heavily during pregnancy) can give
rise
to fetal alcohol syndrome, which includes mental retardation as well as
a range of physical symptoms. Smaller "doses" of prenatal alcohol may
have
negative effects on intelligence even when the full syndrome does not
appear.
Streissguth et al (1989) found that mothers who reported consuming more
than 1.5 oz, of alcohol daily during pregnancy had children who scored
some five points below controls at age four. Prenatal exposure to
aspirin
and antibiotics had similar negative effects in this study.

Perinatal Factors. Complications at
delivery
and other negative perinatal factors may have serious consequences for
development. Nevertheless, because they occur only rarely, they
contribute
relatively little to the population variance of intelligence [Broman et
al, 1975). Down's syndrome, a chromosomal abnormality that produces
serious
mental retardation, is also rare enough to have little impact on the
overall
distribution of test scores.

The correlation between birth weight and later intelligence deserves
particular discussion. In some cases low birth weight simply reflects
premature
delivery; in others, the infant's size is below normal for its
gestational
age. Both factors apparently contribute to the tendency of
low-birth-weight
infants to have lower test scores in later childhood (Lubchenko, 1976).
These correlations are small, ranging from .05 to .13 in different
groups
(Broman et al, 1975). The effects of low birth weight are substantial
only
when it is very low indeed (less than 1500 gm). Premature babies born
at
these very low birth weights are behind controls on most developmental
measures; they often have severe or permanent intellectual deficits
(Rosetti,
1986).

Continuously Rising Test Scores

Perhaps the most striking of all environmental effects is the steady
worldwide
rise in intelligence test performance. Although many psychometricians
had
noted these gains, it was James Mynn (1984, 1987) who first described
them
systematically. His analysis shows that performance has been going up
ever
since testing began. The "Flynn Effect" is now very well documented,
not
only in the United States but in many other technologically advanced
countries.
The average gain is about three IQ points per decade; more than a full
standard deviation since, say, 1940.

Although it is simplest to describe the gains as increases in
population
IQ, this is not exactly what happens. Most intelligence tests are
"re-standardized"
from time to time, in part to keep up with these very gains. As part of
this process the mean score of the new standardization sample is
typically
set to 100 again, so the increase more or less disappears from view. In
this context, the Flynn effect means that if twenty years have passed
since
the last time the test was standardized, people who now score 100 on
the
new version would probably average about 106 on the old one.

The sheer extent of these increases is remarkable, and the rate of
gain
may even be increasing. The scores of nineteen-year-olds in the
Netherlands,
for example, went up more than 8 points--over half a standard
deviation-between
1972 and 1982. What's more, the largest gains appear on the types of
tests
that were specifically designed to be free of cultural influence
(Flynn,
1987). One of these is Raven's Progressive Matrices, an untimed
non-verbal
test that many psychometricians regard as a good measure of g.

These steady gains in intelligence test performance have not always
been accompanied by corresponding gains in school achievement. Indeed,
the relation between intelligence and achievement test scores can be
complex.
This is especially true for the Scholastic Aptitude Test (SAT), in part
because the ability range of the students who take the SAT has
broadened
over time. That change explains some portion, but not all, of the
prolonged
decline in SAT scores that took place from the mid nineteen-sixties to
the early eighties, even as IQ scores were continuing to rise(Flynn,
1984).
Meanwhile, however, other more representative measures show that school
achievement levels have held steady or in some cases actually increased
[Hermstein & Murray, 1994). The National Assessment of Educational
Progress (NAEP), for example, shows that the average reading and math
achievement
of American 13- and l7-year-olds improved somewhat from the early
nineteen-seventies
to 1990 (Grissmer, Kirby, Berends & Williamson, 1994). An analysis
of these data by ethnic group, reported in Section 5, shows that this
small
overall increase actually reflects very substantial gains by Blacks and
Latinos combined with little or no gain by Whites.

The consistent IQ gains documented by Flynn seem much too large to
result
from simple increases in test sophistication. Their cause is presently
unknown, but three interpretations deserve our consideration. Perhaps
the
most plausible of these is based on the striking cultural differences
between
successive generations. Daily life and occupational experience both
seem
more "complex" (Kohn & Schooler, 1973) today than in the time of
our
parents and grandparents. The population is increasingly urbanized;
television
exposes us to more information and more perspectives on more topics
than
ever before; children stay in school longer; almost everyone seems to
be
encountering new forms of experience. These changes in the complexity
of
life may have produced corresponding changes in complexity of mind, and
hence in certain psychometric abilities.

A different hypothesis attributes the gains to modern improvements
in
nutrition. Lynn (1990) points out that large nutritionally-based
increases
in height have occurred during the same period as the IQ gains: perhaps
there have been increases in brain size as well. As we have seen,
however,
the effects of nutrition on intelligence are themselves not firmly
established.

The third interpretation addresses the very definition of
intelligence.
Flynn himself believes that real intelligence-whatever it may
be--cannot
have increased as much as these data would suggest. Consider, for
example,
the number of individuals who have IQ scores of 140 or more. (This is
slightly
above the cutoff used by L.M. Terman (1925) in his famous longitudinal
study of "genius.") In 1952 only 0.38% of Dutch test takers had IQs
over
140; in 1982, scored by the same norms, 9. 12% exceeded this figure!
Judging
by these criteria, the Netherlands should now be experiencing "...a
cultural
renaissance too great to be overlooked" (Flynn, 1987, p.187). So too
should
France, Norway, the United States, and many other countries. Because
Flynn
(1987) finds this conclusion implausibie or absurd, he argues that what
has risen cannot be intelligence itself but only a minor sort of
"abstract
problem solving ability." The issue remains unresolved.

Individual Life Experiences

Although the environmental variables that produce large differences in
intelligence are not yet well understood, genetic studies assure us
that
they exist. With a heritability well below 1.00, IQ must be subject to
substantial environmental influences. Moreover, available heritability
estimates apply only within the range of environments that are
well-represented
in the present population. We already know that some relatively rare
conditions,
like those reviewed earlier, have large negative effects on
intelligence.
Whether there are (now equally rare) conditions that have large
positive
effects is not known.

As we have seen, there is both a biological and a social
environment.
For any given child, the social factors include not only an overall
cultural/
social/school setting and a particular family but also a unique
"micro-environment"
of experiences that are shared with no one else. The adoption studies
reviewed
in Section 3 show that family variables, such as differences in
parenting
style, in the resources of the home, etc., have smaller long-term
effects
than we once supposed. At least among people who share a given SES
level
and a given culture, it seems to be unique individual experience that
makes
the largest environmental contribution to adult IQ differences.

We do not yet know what the key features of those micro-environments
may be. Are they biological? Social? Chronic? Acute? Is there something
especially important in the earliest relations between the infant and
its
caretakers? Whatever the critical variables may be, do they interact
with
other aspects of family life? Of culture? At this point we cannot say,
but these questions offer a fertile area for further research.

...

In this contentious arena, our most useful role may be to remind our
readers that many of the critical questions about intelligence are
still
unanswered. Here are a few of those questions:

Differences in genetic endowment contribute substantially to individual
differences in (psychometric) intelligence, but the pathway by which
genes
produce their effects is still unknown. The impact of genetic
differences
appears to increase with age, but we do not know why.

Environmental factors also contribute substantially to the development
of intelligence, but we do not clearly understand what those factors
are
or how they work. Attendance at school is certainly important, for
example,
but we do not know what aspects of schooling are critical.

The role of nutrition in intelligence remains obscure. Severe childhood
malnutrition has clear negative effects, but the hypothesis that
particular
"micro-nutrients" may affect intelligence in otherwise adequately-fed
populations
has not yet been convincingly demonstrated.

There are significant correlations between measures of information
processing
speed and psychometric intelligence, but the overall pattern of these
findings
yields no easy theoretical interpretation.

Mean scores on intelligence tests are rising steadily. They have gone
up
a full standard deviation in the last fifty years or so, and the rate
of
gain may be increasing. No one is sure why these gains are happening or
what they mean.

The differential between the mean intelligence test scores of Blacks
and
Whites (about one standard deviation, although it may be diminishing)
does
not result from any obvious biases in test construction and
administration,
nor does it simply reflect differences in socio-economic status.
Explanations
based on factors of caste and culture may be appropriate, but so far
have
little direct empirical support. There is certainly no such support for
a genetic interpretation. At present, no one knows what causes this
differential.

It is widely agreed that standardized tests do not sample all forms of
intelligence. Obvious examples include creativity, wisdom, practical
sense
and social sensitivity; there are surely others. Despite the importance
of these abilities we know very little about them: how they develop,
what
factors influence that development, how they are related to more
traditional
measures.

In a field where so many issues are unresolved and so many questions
unanswered,
the confident tone that has characterized most of the debate on these
topics
is clearly out of place. The study of intelligence does not need
politicized
assertions and recriminations; it needs self-restraint, reflection, and
a great deal more research. The questions that remain are socially as
well
as scientifically important. There is no reason to think them
unanswerable,
but finding the answers will require a shared and sustained effort as
well
as the commitment of substantial scientific resources. Just such a
commitment
is what we strongly recommend.